Multi-Sensor Flood Mapping in Urban and Agricultural Landscapes of the Netherlands Using SAR and Optical Data with Random Forest Classifier

Multi-Sensor Flood Mapping in Urban and Agricultural Landscapes of the Netherlands Using SAR and Optical Data with Random Forest Classifier

Floods stand as one of the most harmful natural disasters, which have become more dangerous because of climate change effects on urban structures and agricultural fields. This research presents a comprehensive flood mapping approach that combines multi-sensor satellite data with a machine learning m...

Full description

Saved in:
Bibliographic Details
Main Authors: Omer Gokberk Narin, Aliihsan Sekertekin, Caglar Bayik, Filiz Bektas Balcik, Mahmut Arıkan, Fusun Balik Sanli, Saygin Abdikan
Format: Article
Language:English
Published: MDPI AG 2025-08-01
Series:Remote Sensing
Subjects:
remote sensing
disaster mapping
data fusion
machine learning
flood extent delineation
image classification
Online Access:https://www.mdpi.com/2072-4292/17/15/2712
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://www.mdpi.com/2072-4292/17/15/2712

Similar Items